Computed tomography-based triage of extensive baseline infarction: ASPECTS and collaterals versus perfusion imaging for outcome prediction. Journal of neurointerventional surgery McDonough, R., Elsayed, S., Faizy, T. D., Austein, F., Sporns, P. B., Meyer, L., Bechstein, M., van Horn, N., Nawka, M. T., Schon, G., Kniep, H., Hanning, U., Fiehler, J., Heit, J. J., Broocks, G. 2020


BACKGROUND: Patients presenting with large baseline infarctions are often excluded from mechanical thrombectomy (MT) due to uncertainty surrounding its effect on outcome. We hypothesized that computed tomography perfusion (CTP)-based selection may be predictive of functional outcome in low Alberta Stroke Program Early CT Score (ASPECTS) patients.METHODS: This was a double-center, retrospective analysis of patients presenting with ASPECTS=5who received multimodal admission CT imaging between May 2015 and June 2020. The predicted ischemic core (pCore) was defined as a reduction in cerebral blood flow (rCBF), while mismatch volume was defined using time to maximum (Tmax). The pCore perfusion mismatch ratio (CPMR) was also calculated. These parameters (pCore, mismatch volume, and CPMR), as well as a combined radiological score consisting of ASPECTS and collateral status (ASCO score), were tested in logistic regression and receiver operating characteristic (ROC) analyses. The primary outcome was favorable modified Rankin Scale (mRS) at discharge (=3).RESULTS: A total of 113 patients met the inclusion criteria. The median ischemic core volume was 74.1mL (IQR 43.8-121.8). The ASCO score was associated with favorable outcome at discharge (aOR 3.7, 95%CI 1.8 to 10.7, P=0.002), while no association was observed for the CTP parameters. A model including the ASCO score also had significantly higher area under the curve (AUC) values compared with the CTP-based model (0.88 vs 0.64, P=0.018).CONCLUSIONS: The ASCO score was superior to the CTP-based model for the prediction of good functional outcome and could represent a quick, practical, and easily implemented method for the selection of low ASPECTS patients most likely benefit from MT.

View details for DOI 10.1136/neurintsurg-2020-016848

View details for PubMedID 33168659